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Abstract

Radiation treatment of cancer induces an optical Čerenkov emission throughout the treated volume, which could be used to excite molecular reporters in vivo, allowing molecular sensing of tissue response during fractionated therapy. In this Letter, the idea that spatial mapping of this signal can be achieved with tomographic recovery of the fluorophore distribution is tested for the first time using 6 MV photons from a linear accelerator in a heterogeneous tissue phantom. Čerenkov light excited fluorophores throughout the tissue phantom, and diffuse tomography was used to recover images. Measurements from 13 locations were used, with spectrometer detection and spectral fitting, to separate the fluorophore emission from the Čerenkov continuum. Fluorescent diffuse tomographic images showed a linear response between the concentration and the reconstructed values. The potential to apply this molecular imaging in treatment with molecular reporters appears promising.

Figures (3)

Fig. 1. (a) Schematic of the experimental setup shows the location of the phantom and measurement devices. (b) The phantom schematic shows the region of the phantom where Čerenkov light would be generated in a three-dimensional volume. (c) The top view of the phantom has a white-light image of the experimental setup with the phantom exterior highlighted with red.

Fig. 2. LS fitting of the background Čerenkov radiation and the fluorophore emission spectrum were done for each detector location shown in (c). (a) Example of 0.1mg/mL concentration fitting. (b) Example of 0.8mg/mL concentration fitting. (d) Integrated intensity of the signal measured in each detector for increasing concentrations of fluorophore in the anomaly.

Fig. 3. (a) Calculated field of Čerenkov radiation is shown in the plane of the detection fibers. (b) The reconstructed images are shown when using no spatial information for each of the concentrations marked. (c) The linear relationship between the concentration of the anomaly and the reconstructed values are shown in the graph.